互信息作為衡量?jī)煞鶊D像配準(zhǔn)的相似性測(cè)度函數(shù)，當(dāng)兩幅圖像配準(zhǔn)時(shí)，互信息達(dá)到最大值。該文提出了基于互信息腦功能磁共振圖像配準(zhǔn)新方法，采用了無(wú)需計(jì)算梯度的Powell直接搜索算法，并通過(guò)多分辨的方式加快了圖像配準(zhǔn)速度。磁共振的配準(zhǔn)實(shí)驗(yàn)證明，互信息法能準(zhǔn)確地實(shí)現(xiàn)多模態(tài)醫(yī)學(xué)圖像的配準(zhǔn)，并且能達(dá)到亞像素的精度。
關(guān) 鍵 詞 功能磁共振; 圖像配準(zhǔn); 互信息; 亞像素

Abstract The functional magnetic resonance imaging (fMRI) image registration is a key technology in the study of the human brain function. In this article, we present a new fMRI image registration algorithm based on the mutual information. The mutual information is specified as scaling the similarity of two images registration. The mutual information of two images reaches to maximization when the two images are registered. Powell direct searching and multi-scale algorithm are introduced to accelerate the image registration speed without calculating gradient algorithm. Simulative experiments of fMRI image registration demonstrate that this method can precisely achieve the multimodal medical image registration, and can reach sub-pixel precision
Key words functional magnetic resonance imaging (fMRI); image registration; mutual information; sub- pixel